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A multiplicative gradient-based anisotropic diffusion approach for speckle noise removal

机译:基于乘法梯度的各向异性扩散方法去除斑点噪声

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We propose a novel directional diffusion method for speckle noise removal that uses the multiplicative gradient as an edge detector and operates on a moving orthonormal basis issued by a structure tensor based-approach and stochastic modelling. The method has good speckle removal and edge preservation properties and it can be used for filtering ultrasound, optical coherence tomography medical images or other types of images degraded by speckle, such as those acquired in Synthetic Aperture Radar (SAR) imaging systems. The effectiveness of our approach in speckle removal applications is demonstrated experimentally on computer generated and on real ultrasound images through comparisons with state-of-the-art Partial Differential Equations (PDE) and non-PDE-based methods.
机译:我们提出了一种用于斑点噪声去除的新颖方向性扩散方法,该方法使用乘法梯度作为边缘检测器,并在基于结构张量的方法和随机建模发出的正交运动基础上进行操作。该方法具有良好的斑点去除和边缘保留特性,可用于过滤超声,光学相干断层扫描医学图像或因斑点而退化的其他类型的图像,例如在合成孔径雷达(SAR)成像系统中获得的图像。通过与最新的偏微分方程(PDE)和基于非PDE的方法进行比较,在计算机生成的图像和实际超声图像上通过实验证明了我们的方法在去斑应用中的有效性。

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